Please use this identifier to cite or link to this item: https://doi.org/10.1109/TSMCC.2007.900660
Title: Adaptive control of mechanical systems using neural networks
Authors: Huang, S. 
Tan, K.K. 
Lee, T.H. 
Putra, A.S. 
Keywords: Adaptive control
Decentralized control
Mechanical systems
Neural networks (NNs)
Issue Date: Sep-2007
Source: Huang, S.,Tan, K.K.,Lee, T.H.,Putra, A.S. (2007-09). Adaptive control of mechanical systems using neural networks. IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews 37 (5) : 897-903. ScholarBank@NUS Repository. https://doi.org/10.1109/TSMCC.2007.900660
Abstract: In this paper, we consider the decentralized adaptive control design problem for uncertain mechanical systems, where uncertainty may arise due to isolated subsystem and/or interconnections among subsystems. Radial basis function neural networks are used to approximate the nonlinear functions to include both dynamic and interconnection uncertainties in each subsystem. The stability of the thus designed control system can be guaranteed by a rigid proof. Finally, a simulation example is given to illustrate the effectiveness of the proposed algorithm. © 2007 IEEE.
Source Title: IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews
URI: http://scholarbank.nus.edu.sg/handle/10635/54891
ISSN: 10946977
DOI: 10.1109/TSMCC.2007.900660
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

11
checked on Dec 5, 2017

WEB OF SCIENCETM
Citations

4
checked on Nov 3, 2017

Page view(s)

27
checked on Dec 9, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.